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Keywords = Claude Mythos

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29 pages, 3247 KB  
Article
Mythos-Class AI and Blockchain Systemic Risk: A Comparative Analysis of Bitcoin and Ethereum/L2 Architectures
by Robert Campbell
Blockchains 2026, 4(3), 11; https://doi.org/10.3390/blockchains4030011 - 10 Jul 2026
Viewed by 610
Abstract
Cryptocurrency market infrastructure—public blockchains and cross-chain bridges supporting tens of billions in liquidity—is monitored as a systemic-risk surface by the Financial Stability Board and equivalent bodies, with defensive posture calibrated against human-level adversaries. Anthropic’s April 2026 release of Claude Mythos Preview has prompted [...] Read more.
Cryptocurrency market infrastructure—public blockchains and cross-chain bridges supporting tens of billions in liquidity—is monitored as a systemic-risk surface by the Financial Stability Board and equivalent bodies, with defensive posture calibrated against human-level adversaries. Anthropic’s April 2026 release of Claude Mythos Preview has prompted institutional response across financial regulation but no blockchain-specific analytical framework. This paper develops one by defining Mythos-class as a vendor-neutral capability profile: a set of frontier autonomous offensive capabilities specified independently of any single model or vendor (defined by five constituent capability primitives). The central analytical claim is friction inversion: the patch primitives, segmentation, vendor-coordinated disclosure, and credential rotation that constrain Mythos-class capability in conventional IT environments are structurally absent on-chain. This makes blockchain exposure positioned differently in kind, not degree, from enterprise IT. The paper instantiates this finding against Bitcoin and Ethereum/L2 architectures through analysis of four major bridge exploits totaling over $1.74 billion in losses. Vendor-neutral defensive and governance frameworks defined against the capability profile rather than any specific model release are the correct unit of analysis. On this basis the paper offers general recommendations for protocol governance, audit and verification cadence, and regulatory posture, developed as an analytical framework rather than as empirically validated risk estimates. Full article
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34 pages, 2143 KB  
Hypothesis
Mythos-Class Frontier Models and the Compression of Post-Quantum Cryptography Migration Timelines
by Robert Campbell
Cryptography 2026, 10(3), 41; https://doi.org/10.3390/cryptography10030041 - 18 Jun 2026
Cited by 1 | Viewed by 2142
Abstract
Post-Quantum Cryptography (PQC) migration to National Institute of Standards and Technology (NIST) Federal Information Processing Standards (FIPS) 203, 204, and 205 under the National Security Agency (NSA) Commercial National Security Algorithm Suite (CNSA) 2.0 is a multi-year, multi-domain transformation across cloud, enterprise, embedded, [...] Read more.
Post-Quantum Cryptography (PQC) migration to National Institute of Standards and Technology (NIST) Federal Information Processing Standards (FIPS) 203, 204, and 205 under the National Security Agency (NSA) Commercial National Security Algorithm Suite (CNSA) 2.0 is a multi-year, multi-domain transformation across cloud, enterprise, embedded, operational technology (OT), tactical, and national-security systems. Anthropic’s Claude Mythos Preview (April 2026) introduces artificial intelligence (AI)-accelerated cybersecurity capabilities that intersect this migration directly, performing autonomous reasoning against previously unknown vulnerabilities in production software—a qualitative departure from signature-based and static and dynamic application security testing (SAST/DAST) tooling. Drawing on federal guidance from NIST, NSA, the Office of Management and Budget (OMB), and the Cybersecurity and Infrastructure Security Agency (CISA), and on independent analyses from the Centre for Emerging Technology and Security (CETaS) and the UK AI Security Institute, we present a lifecycle and architecture analysis of how Mythos-class models alter PQC migration timelines, risk surfaces, lifecycle dependencies, and architectural constraints. Modeling Mythos as both accelerator and destabilizer, we derive an analytic projection of a compressed two-to-four-year migration window for highest-exposure systems, against traditional baselines of five-to-ten years for small organizations and twelve-to-fifteen-plus years for large enterprises. The compression collapses human-labor bottlenecks in discovery, planning, and code modification, not cryptography itself. We propose a lifecycle-aligned migration model, an updated cost model, and governance requirements for frontier-model access. The binding constraint shifts domain-conditionally: defender capacity at adversary tempo governs software-analytical phases, while non-compressible external cadence governs embedded and regulated domains. Full article
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58 pages, 8495 KB  
Article
Detection and Mitigation of Mythos-Class Frontier Model Capabilities: A Layered Reference Architecture
by Robert Campbell
Computers 2026, 15(6), 331; https://doi.org/10.3390/computers15060331 - 22 May 2026
Cited by 1 | Viewed by 2734
Abstract
Anthropic’s April 2026 Claude Mythos Preview release established a new operational threat category: frontier AI systems whose extended-context reasoning, recursive self-correction, native system-tool integration, and agentic scaffolding render dominant AI safety paradigms—RLHF, output filtering, contractual access vetting, human-in-the-loop supervision—insufficient as sole controls. This [...] Read more.
Anthropic’s April 2026 Claude Mythos Preview release established a new operational threat category: frontier AI systems whose extended-context reasoning, recursive self-correction, native system-tool integration, and agentic scaffolding render dominant AI safety paradigms—RLHF, output filtering, contractual access vetting, human-in-the-loop supervision—insufficient as sole controls. This paper develops a defense-in-depth reference architecture against that category, structured around four named contributions: a five-indicator operational definition of the Mythos-class (capability conjoined with scaffold, access pattern, autonomy depth, and persistence); the Mythos-Class Posture Rubric (MCPR), a three-tier detection framework spanning evaluation, deployment, and runtime with explicit routing to mitigation layers; a four-layer mitigation stack comprising the Vetted-Access Operational Pattern (VAOP), Authority-Bound Output Release (ABOR) cryptographically grounded in FIPS 203/204/205 post-quantum primitives, and the Compute-Plane Isolation Profile (CPIP); and an integrated architecture that crosswalks to the NIST AI Risk Management Framework, NIST Cybersecurity Framework 2.0, and CISA Zero Trust Maturity Model 2.0. The architecture is applied to three deployment surfaces—post-quantum cryptography migration, federal AI supply-chain assurance, and critical-infrastructure operational technology defense—demonstrating that the four contributions generalize across heterogeneous operational contexts. The contribution is a reference design rather than a deployed system; limitations, falsifiability criteria, and a research agenda for empirical refinement are developed. Full article
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